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Generating correlated discrete ordinal data using R and SAS IML

Overview of attention for article published in Computer Methods & Programs in Biomedicine, July 2011
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Title
Generating correlated discrete ordinal data using R and SAS IML
Published in
Computer Methods & Programs in Biomedicine, July 2011
DOI 10.1016/j.cmpb.2011.06.003
Pubmed ID
Authors

Noor Akma Ibrahim, Suliadi Suliadi

Abstract

Correlated ordinal data are common in many areas of research. The data may arise from longitudinal studies in biology, medical, or clinical fields. The prominent characteristic of these data is that the within-subject observations are correlated, whilst between-subject observations are independent. Many methods have been proposed to analyze correlated ordinal data. One way to evaluate the performance of a proposed model or the performance of small or moderate size data sets is through simulation studies. It is thus important to provide a tool for generating correlated ordinal data to be used in simulation studies. In this paper, we describe a macro program on how to generate correlated ordinal data based on R language and SAS IML.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Lecturer 2 29%
Other 1 14%
Professor 1 14%
Researcher 1 14%
Other 0 0%
Readers by discipline Count As %
Mathematics 2 29%
Medicine and Dentistry 2 29%
Social Sciences 1 14%
Engineering 1 14%
Unknown 1 14%